Title:
Crisis-Induced Corruption and Citizens’ Evaluations of Government COVID-19 Response in Africa: The Moderating Role of Corruption Control

Author: 
Elvis Bisong Tambe, Department of Political Science, Linnaeus University, Sweden
Email: elvisbisong.tambe@lnu.se
Journal: Japanese Journal of Political Science (Accepted 2025)


1. Overview

This dataset and replication package provide the materials necessary to reproduce the empirical analyses reported in the article “Crisis-Induced Corruption and Citizens’ Evaluations of Government COVID-19 Response in Africa: The Moderating Role of Corruption Control,” accepted for publication in the Japanese Journal of Political Science (2025). It examines how perceptions of crisis-induced corruption during the COVID-19 pandemic influenced citizens’ evaluations of government performance across 39 African...


2. File Structure

      Data Files: 
     (i) Afrobarometer_R9_clean_subset.dta – Cleaned dataset used in all analyses (includes individual- and country-level variables).
     (ii) WGI_Control_of_Corruption.csv.xlsx – Source data for the World Bank Control of Corruption indicator.
     (iii) V-Dem_Liberal_Democracy_Index.csv.xlsx – Source data for the V-Dem Liberal Democracy Index indicator.

     Code Files:
     (i) analysis_table1.do – Mixed-effects regressions (Table 1).
     (ii) figure4.do – Reproduces Figure 4 (scatter plot: perceived COVID-19 corruption vs. control of corruption).
     (iii) figure5.do – Reproduces Figure 5 (predicted effect of COVID-19 corruption on government mismanagement).
     (iv) figure6.do – Reproduces Figure 6 (predicted effects including individual-level controls).
      (v) figure7.do – Reproduces Figure 7 (cross-level interaction: COVID-19 corruption × control of corruption).

     Notes:
     The cleaned dataset already contains all variables used in the analyses. 
     The two CSV files are included for verification and transparency.
     Actual figures and tables are not included; they appear in the published article.


3. Data Sources

     (1) Afrobarometer Round 9 (2021–2023) — https://www.afrobarometer.org/data/merged-data/ 
         Individual-level public-opinion survey data used for all analyses.
     (2) World Bank Governance Indicators – Control of Corruption (year-matched to fieldwork) — https://www.govindicators.org (Accessed 1 February 2024)
         The file WGI_Control_of_Corruption.csv contains the country-year values used for merging.
     (3) Varieties of Democracy (V-Dem) Liberal Democracy Index (v13 or later) — https://v-dem.net/data
         The file VDem_Liberal_Democracy_Index.csv provides the corresponding country-year scores.

     Variable Documentation:
     The dataset includes recoded and renamed variables used in the analyses. The exact Afrobarometer question wordings and coding details for all   
     variables (including the dependent and independent variables) are provided in the Online Appendix of the published article.


4. Software

     - Stata 19.5 (tested; works on Stata 16 or later)
     - Operating System: Windows
     - Ado Dependencies: none required beyond base Stata


5. Replication Instructions

   1. Ensure all files are placed in the structure above.
      • Afrobarometer_R9_clean_subset.dta is the dataset used by all scripts.
      • WGI_Control_of_Corruption.csv and VDem_Liberal_Democracy_Index.csv are provided only for reference and are not directly called in the code.

   2. Open the relevant .do file(s) in Stata 19.5 (or later).
   Each script reproduces the results associated with its table or figure:
      • analysis_table1.do – Mixed-effects regression models reported in Table 1.
      • figure4.do – Scatter plot of average perceived COVID-19 corruption and Control of Corruption (WGI).
      • figure5.do – Predicted relationship between perceived COVID-19 corruption and government mismanagement.
      • figure6.do – Predicted effects including individual-level controls.
      • figure7.do – Cross-level interaction between perceived COVID-19 corruption and Control of Corruption.

   3. Running each script will load the cleaned dataset, estimate the specified models, and generate the corresponding statistical output and graphs  
      within Stata.

   4. The actual figures (4–7) and Table 1 are not included in this archive, as they appear in the published article.


6. License

This replication package is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) License.
Please attribute as: Tambe (2025), JJPS Replication Package.


7. Citation

Tambe, Elvis Bisong (2025). Replication Data for “Crisis-Induced Corruption and Citizens’ Evaluations of Government COVID-19 Response in Africa: The Moderating Role of Corruption Control.” Japanese Journal of Political Science. JJPS Dataverse. DOI: to be assigned by Dataverse.


8. Notes

- All data included are publicly available and contain no restricted or sensitive information.
- The code reproduces the main models and figures reported in the article; robustness and appendix analyses can be provided on request.
